cdf: Empirical Scedasis Distribution Function

In extremis: Statistics of Extremes

Description

This function computes the empirical scedasis distribution function.

Usage

cdf(Y, threshold = quantile(Y[, 2], 0.95))

Arguments

Y	data frame from which the estimate is to be computed; first column corresponds to time and the second to the variable of interest.
threshold	value used to threshold the data y; by default threshold = quantile(Y[, 2], 0.95).

Details

The empirical scedasis distribution function was introduced by Einmahl et al (2016).

Value

C	empirical scedasis distribution function.
w	standardized indices of exceedances.
k	number of exceedances above a threshold.
Y	raw data.

The plot method depicts the empirical cumulative scedasis function, and the reference line for the case of constant frequency of extremes over time (if uniform = TRUE).

Author(s)

Miguel de Carvalho

References

Einmahl, J. H., Haan, L., and Zhou, C. (2016) Statistics of heteroscedastic extremes. Journal of the Royal Statistical Society: Ser. B, 78(1), 31–51.

Examples

data(sp500)
attach(sp500)
Y <- data.frame(date[-1], -diff(log(close)))
fit <- cdf(Y)
plot(fit)
plot(fit, original = FALSE)

extremis documentation built on Nov. 27, 2020, 9:07 a.m.